Key takeaways
- H2O Driverless AI can build churn and lapse models from your own policy, billing, claims and contact history, with a reason code on every score.
- A second model can predict which retention offer each at-risk policyholder is likely to accept, so incentives go where they change the outcome.
- Scores feed the CRM, agent desktop and campaign tools you already run; none of them is replaced.
- Nationwide reported more than 500,000 models instantiated and 25 billion predictions scored over a decade, across use cases that included customer retention.
Your best customers leave quietly
Your most valuable households often hold several policies, so one lapse can take a home, an auto and an umbrella policy with it. Many of them never call before they go; they simply do not renew.
Rules built on known behaviors, such as a missed payment or a recent rate increase, catch some of the leavers. They miss many others, and they send expensive incentives to policyholders who were going to stay anyway.